CN113537754A - Efficient intelligent customized furniture order scheduling method, device, medium and equipment - Google Patents
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Abstract
The invention provides a method, a device, a medium and equipment for efficiently and intelligently customizing furniture orders and scheduling production; the method comprises the following steps: acquiring a new order; splitting the newly added order into minimum parts; extracting a plurality of parts from a database to be scheduled to be produced to combine into an initial test combination; analyzing the current test combination to obtain an evaluation score; if the evaluation score of the current test combination is higher than that of the undetermined combination, updating the undetermined combination into the current test combination; extracting part of parts in a database to be scheduled to replace part of parts which are not replaced in the database to be scheduled to be combined to form a new test combination, and then repeatedly evaluating and scoring; when the cycle is over, the pending combination is set as the preferred combination. The method can realize the automatic decomposition of orders and the automatic production scheduling function, and comprehensively considers various parts to perform production scheduling, thereby reducing the workload of production scheduling personnel, reducing the labor cost and improving the production scheduling efficiency.
Description
Technical Field
The invention relates to the technical field of furniture processing, in particular to a method, a device, a medium and equipment for efficiently and intelligently customizing an order of furniture.
Background
With the improvement of living standard of people, personalized customized home starts to enter the life of people; the custom-made furniture is also produced from the original single-product custom-made production and gradually develops to a whole-house custom-made production mode. At present, whether small-batch orders or large-scale orders are formed, planning personnel with rich experience often select proper orders from a large number of orders to combine the orders into a processing batch for production arrangement; in this process, the selection of which combinations of tests are entirely in the experience of the planner; however, even if the experience of the planning personnel is more abundant, the optimal experimental combination scheme cannot be selected from a large number of orders. And as the order size is larger, the more work and time are required to assemble a processing lot. But the delivery time of personalized home customization is short, and the prior art cannot meet the requirement of large-scale production.
In addition, the product types of the custom-made furniture are diversified and developed at the present stage, and various types of products are independently scheduled and produced in a complex production process, so that the custom-made furniture is not suitable for the production of the custom-made furniture at present; in the field of intelligent furniture manufacturing, the trend of improving the utilization rate and the production efficiency of plates by realizing intelligent mixed production scheduling is inevitable. Therefore, it is highly desirable to design a customized furniture scheduling scheme that can achieve mixed scheduling, reduce labor cost, and improve scheduling efficiency.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide a method, a device, a medium and equipment for efficiently and intelligently customizing furniture orders; the method can realize the automatic order decomposition and automatic production scheduling functions, comprehensively considers various parts to perform production scheduling, can reduce the workload of production scheduling personnel, reduce the labor cost, improve the production scheduling efficiency, and can avoid the problems of mistakes and omissions of manual production scheduling.
In order to achieve the purpose, the invention is realized by the following technical scheme: an efficient intelligent customized furniture order scheduling method is characterized by comprising the following steps: the method comprises the following steps:
s1, acquiring a newly added order to obtain a furniture design drawing included in the newly added order;
s2, splitting the newly added order into minimum parts according to furniture design drawings, and marking part information; the part information comprises part names, part categories, color categories, sizes, outer contour types, hole and groove types and order characteristic information of corresponding orders; the order characteristic information comprises an order number and a delivery date;
s3, storing newly added order parts, unmanaged parts and reworked parts in a to-be-scheduled database, and removing order returned order parts from the to-be-scheduled database;
s4, extracting a plurality of parts from the database to be scheduled to combine into an initial test combination, and setting the initial test combination as an initialized undetermined combination;
s5, analyzing the current test combination to obtain an evaluation score;
and step S6, judging whether the current test combination is the initial test combination:
if yes, directly jumping to the step S7;
otherwise, the evaluation score of the current trial combination is compared with the evaluation score of the pending combination: if the evaluation score of the current test combination is higher than that of the undetermined combination, updating the undetermined combination into the current test combination; if the evaluation score of the current test combination is lower than or equal to the evaluation score of the undetermined combination, the original undetermined combination is reserved;
and step S7, judging whether to continue circulation:
if yes, extracting part of parts in the database to be scheduled to produce, and replacing part of parts which are not replaced in the to-be-scheduled combination to form a new test combination; returning the replaced parts in the pending combination to the pending production database; then jumping to step S5;
otherwise, the combination to be determined is set as the preferred combination, the production is performed according to the preferred combination, and the parts in the database to be produced are set as the parts which are not produced.
Preferably, in step S2, splitting the newly added order into minimum parts according to the furniture design drawing, where the splitting is: splitting the newly added order into various furniture, splitting the furniture into minimum parts according to a furniture design drawing, wherein a part set of the newly added order is represented by I:
I＝{DiPjHk}(i＝1,2,3,…n，j＝1,2,3,…n，k＝1,2,3,…n)
wherein DiIndicates an order number, PjDenotes the name of furniture HkRepresenting the smallest part.
Preferably, in step S5, the analyzing of the current test combination to obtain an evaluation score means:
firstly, analyzing the reasonable degree of combination of the current test combination to obtain a score A:
A＝A1+A2+A3+A4+A5+A6+A7+A8
wherein A is1Representing a part color category score; a. the2Representing the same category score of the parts; a. the3A score representing the delivery date tension level; a. the4Representing a part quantity score; a. the5The score of the similarity degree of the sizes of the parts is expressed; a. the6Representing a part type facies proximity score; a. the7The score of the similarity degree of the outer contour types of the parts is represented; a. the8The score of the similarity degree of the types of the hole grooves of the parts is represented;
and analyzing the production capacity of the test combination to obtain a score B:
B＝B1+B2+B3+B4+B5
wherein, B1Representing the score of the sufficiency of the materials corresponding to the parts; b is2Representing the reasonable degree score of the arrangement of the parts corresponding to the processing equipment; b is3Representing the reasonable degree score of the arrangement of the corresponding production workers of the parts; b is4Representing the productivity efficiency score of the processing equipment corresponding to the part; b is5A score representing the degree of man-hour engagement;
adding the score A and the score B according to a set weight to obtain an evaluation score:
Score＝α·A+(1-α)·B
wherein α is a reduction factor.
Preferably, in the score B, B1The acquisition method comprises the following steps: calculating the materials and the quantity of the materials required by production according to the part types, the color types and the sizes of all parts in the test combination; comparing the calculated materials and the quantity of each material with the stock of the materials in the material database to obtain a component corresponding material sufficiency degree score B1；
B2The acquisition method comprises the following steps: obtaining processing equipment required by production through part types, color types, sizes, outer contour types and hole and groove types of all parts in the test combination; obtaining the scheduling condition of the processing equipment required by production so as to obtain the reasonable degree score B of the arrangement of the processing equipment corresponding to the part2；
B3The acquisition method comprises the following steps: obtaining a corresponding production processing station through the part category, the color category, the size, the outer contour type and the hole and groove type of each part in the test combination; obtaining the scheduling condition of workers producing corresponding processing stations, thereby obtaining the reasonable degree score B of arrangement of the workers producing corresponding parts3；
B4The acquisition method comprises the following steps: obtaining processing equipment required by production through part types, color types, sizes, outer contour types and hole and groove types of all parts in the test combination; obtaining the production condition of the processing equipment required by production, comparing the actual yield of the processing equipment required by production with the predicted yield of the experimental combination with the design yield of the processing equipment to obtain a capacity efficiency score B of the processing equipment corresponding to the part4；
B5The acquisition method comprises the following steps: calculating the expected production time of all parts in the test combination on the processing equipment required by production or the processing station corresponding to the production so as to obtain a working hour matching degree score B5。
Preferably, in the step S7, the step of determining whether to continue the loop includes: judging the evaluation score of the undetermined combination: if the evaluation score of the undetermined combination is higher than the set optimal evaluation score, or the variance between the mean value of the evaluation scores of the continuous N-generation test combinations and the evaluation score of the current test combination is smaller than the set threshold, ending the circulation; otherwise, the loop continues.
Preferably, in step S7, extracting some parts in the database to be scheduled includes: respectively judging the priority of each part in the to-be-scheduled production database; extracting part of parts with the highest priority in a database to be scheduled;
in step S7, the replaced parts ratio is less than or equal to the parts ratio replaced last time.
Preferably, an expert system knowledge base comprising a plurality of rule units is established; in the step S4, more than one rule unit in the expert system knowledge base is selected, and a plurality of parts are extracted from the database to be scheduled according to the selected rule units to be combined into an initial test combination;
after the preferred combination is obtained in step S7, the rule units of the expert system knowledge base are updated according to the preferred combination, or new rule units are generated and added to the expert system knowledge base.
The expert system knowledge base can set a large number of production scheduling rules, including production scheduling knowledge and experience and features extracted by obtaining the optimal combination each time, so that the initial test combination is combined by combining the expert system knowledge base, a scheme close to the optimal combination can be obtained, and the time for solving the optimal combination is greatly shortened.
The utility model provides a high-efficient intelligence customization furniture order scheduling device which characterized in that includes:
the order acquisition module is used for acquiring a newly added order to obtain a furniture design drawing contained in the newly added order;
the order decomposition module is used for splitting the newly added order into minimum parts according to the furniture design drawing and marking part information; the part information comprises part names, part categories, color categories, sizes, outer contour types, hole and groove types and order characteristic information of corresponding orders; the order characteristic information comprises an order number and a delivery date;
the to-be-scheduled production database processing module is used for storing newly-added order parts, non-scheduled production parts and reworked parts in the to-be-scheduled production database and removing order-returned order parts from the to-be-scheduled production database;
the test combination initialization module is used for extracting a plurality of parts from the database to be scheduled to be produced to be combined into an initial test combination, and setting the initial test combination as an initialized undetermined combination;
the test combination updating module is used for extracting part of parts in the database to be scheduled and replacing part of parts which are not replaced in the database to be scheduled to combine into a new test combination; returning the replaced parts in the pending combination to the pending production database;
the combination scoring module is used for analyzing the current test combination to obtain an evaluation score;
the score comparison module is used for comparing the evaluation score of the current test combination with the evaluation score of the undetermined combination: if the evaluation score of the current test combination is higher than that of the undetermined combination, updating the undetermined combination into the current test combination; if the evaluation score of the current test combination is lower than or equal to the evaluation score of the undetermined combination, the original undetermined combination is reserved;
and the output module is used for setting the combination to be determined as the preferred combination when the cycle is finished, performing production scheduling according to the preferred combination, and setting the parts in the database to be scheduled as the parts not scheduled.
A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, causes the processor to perform the above efficient intelligent customized furniture order placement method.
A computing device comprising a processor and a memory for storing a program executable by the processor, wherein the processor implements the above method for efficiently and intelligently scheduling orders for customized furniture when executing the program stored in the memory.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the automatic order decomposition and automatic production scheduling functions can be realized, various types of parts are comprehensively considered for production scheduling, the workload of production scheduling personnel can be reduced, the labor cost is reduced, the production scheduling efficiency is improved, and the problem of error and leakage in manual production scheduling can be avoided;
2. the analysis of the test combination comprises the analysis of the reasonable degree and the production capacity of the combination, the convenient degree and the efficient operation of the production are considered, and the load capacity of each processing device and the workload of production workers are considered, so that the processing devices and the production workers are reasonably arranged; the production efficiency can be effectively improved;
3. the invention sets an expert system knowledge base to assist the combination scheduling and optimization of the parts, thereby further improving the scheduling efficiency and obtaining a better scheduling result.
Drawings
FIG. 1 is a flow chart of an efficient intelligent customized furniture order scheduling method of the present invention;
FIG. 2 is a schematic structural diagram of a to-be-scheduled database in the efficient intelligent customized furniture order scheduling method according to the invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Example one
As shown in fig. 1, the method for scheduling an order of an intelligent customized furniture in an efficient manner according to the embodiment includes the following steps:
and S1, acquiring the newly added order and obtaining the furniture design drawing included in the newly added order.
S2, splitting the newly added order into minimum parts according to furniture design drawings, and marking part information; the part information comprises part names, part categories, color categories, sizes, outer contour types, hole and groove types and order characteristic information of corresponding orders; the order characteristics information includes an order number and a delivery date.
Specifically, the newly added order is split into furniture, the furniture is split into the minimum parts according to a furniture design drawing, and a part set of the newly added order is represented by I:
I＝{DiPjHk}(i＝1,2,3,…n，j＝1,2,3,…n，k＝1,2,3,…n)
wherein DiIndicates an order number, PjDenotes the name of furniture HkRepresenting the smallest part.
Taking an order as an example, the order includes: bedside rug, wardrobe, and wooden chair. Firstly, splitting an order into a bedside cabinet, a wardrobe and a wooden chair, and splitting the bedside cabinet, the wardrobe and the wooden chair respectively, wherein I ═ D1P1H1(bedside table bottom plate), D1P1H2(bedside table backboard) D1P1H3(bedside table partition plate), D1P1H4(bedside table top plate), D1P1H5(bedside cupboard left and right side plates), D1P2H1(wardrobe Wide side plate), D1P2H2(wardrobe back plate), D1P2H3(wardrobe bottom plate), D1P2H4(wardrobe ceiling), D1P2H5(wardrobe double Link), D1P2H6(Single Link of wardrobe), D1P2H7(wardrobe L-shaped Board), D1P2H7(wardrobe three-section rail), D1P3H1(wooden chair backboard) D1P3H2(wooden chair plate), D1P3H3(wooden chair legs).
And S3, simultaneously storing the newly added order parts, the unmanaged parts and the reworked parts in a database to be scheduled, and removing the order returned order parts from the database to be scheduled, as shown in FIG. 2. The method can keep the consistency of the parts in the database to be scheduled and the dynamic change of the actual production demand.
And S4, extracting a plurality of parts from the database to be scheduled to combine into an initial test combination, and setting the initial test combination as the initialized pending combination.
And S5, analyzing the current test combination to obtain an evaluation score.
Specifically, firstly, the combination reasonableness of the current test combination is analyzed to obtain a score a:
A＝A1+A2+A3+A4+A5+A6+A7+A8
wherein A is1Indicating the color class score of the part, the smaller the number of color classes, A1The higher; a. the2The score of the same type of the parts is represented, and the more the number of the parts in the same type of the parts is, the A2The higher; a. the3Showing the score of tension degree of delivery date, the more tense the delivery date of the part is, A3The higher; a. the4Represents the score of the number of parts, the more the number of parts is, A4The higher; a. the5The score of the similarity degree of the sizes of the parts is shown, and the closer the sizes of the parts are, the more A5The higher; a. the6Representing the proximity score of the part type, A being the closer the part type is6The higher; a. the7The score of the similarity degree of the outline types of the parts is shown, and the more similar the outline types of the parts are, the A7The higher; a. the8The score of the similarity degree of the hole and groove types of the parts is shown, and the more similar the hole and groove types of the parts are, A8The higher;
and analyzing the production capacity of the test combination to obtain a score B:
B＝B1+B2+B3+B4+B5
wherein, B1Representing the score of the sufficiency of the materials corresponding to the parts; b is2Representing the reasonable degree score of the arrangement of the parts corresponding to the processing equipment; b is3Representing the reasonable degree score of the arrangement of the corresponding production workers of the parts; b is4Representing the productivity efficiency score of the processing equipment corresponding to the part; b is5A score representing the degree of man-hour engagement;
B1the acquisition method comprises the following steps: calculating the materials and the quantity of the materials required by production according to the part types, the color types and the sizes of all parts in the test combination; comparing the calculated materials and the quantity of each material with the stock of the materials in the material databaseThen, the score B of the sufficiency degree of the corresponding materials of the parts is obtained1(ii) a The more sufficient the material is, B1The higher;
B2the acquisition method comprises the following steps: obtaining processing equipment required by production through part types, color types, sizes, outer contour types and hole and groove types of all parts in the test combination; obtaining the scheduling condition of the processing equipment required by production so as to obtain the reasonable degree score B of the arrangement of the processing equipment corresponding to the part2(ii) a The fewer batches to be processed in the processing equipment, the B2The higher;
B3the acquisition method comprises the following steps: obtaining a corresponding production processing station through the part category, the color category, the size, the outer contour type and the hole and groove type of each part in the test combination; obtaining the scheduling condition of workers producing corresponding processing stations, thereby obtaining the reasonable degree score B of arrangement of the workers producing corresponding parts3(ii) a The fewer batches to be processed by production workers, the B3The higher;
B4the acquisition method comprises the following steps: obtaining processing equipment required by production through part types, color types, sizes, outer contour types and hole and groove types of all parts in the test combination; obtaining the production condition of the processing equipment required by production, comparing the actual yield of the processing equipment required by production with the predicted yield of the experimental combination with the design yield of the processing equipment to obtain a capacity efficiency score B of the processing equipment corresponding to the part4(ii) a The closer the ratio is to 100%, the closer B4The higher;
B5the acquisition method comprises the following steps: calculating the expected production time of all parts in the test combination on the processing equipment required by production or the processing station corresponding to the production so as to obtain a working hour matching degree score B5；
And then adding the score A and the score B according to a set weight to obtain an evaluation score:
Score＝α·A+(1-α)·B
wherein, α is a folding factor, and the folding factor can be adjusted appropriately according to the actual situation.
And step S6, judging whether the current test combination is the initial test combination:
if yes, directly jumping to the step S7;
otherwise, the evaluation score of the current trial combination is compared with the evaluation score of the pending combination: if the evaluation score of the current test combination is higher than that of the undetermined combination, updating the undetermined combination into the current test combination; if the evaluation score of the current trial combination is lower than or equal to the evaluation score of the pending combination, the original pending combination is reserved.
Step S7, judging whether to continue circulation; the method specifically comprises the following steps: judging the evaluation score of the undetermined combination: if the evaluation score of the undetermined combination is higher than the set optimal evaluation score, or the variance between the mean value of the evaluation scores of the continuous N-generation test combinations and the evaluation score of the current test combination is smaller than the set threshold, ending the circulation; otherwise, continuing to circulate;
if the circulation is continued, the priority judgment is respectively carried out on each part in the to-be-scheduled production database; extracting part of parts with the highest priority in a database to be scheduled to produce to replace part of parts which are not replaced in a combination to be scheduled so as to combine a new test combination; the proportion of the replaced parts is less than or equal to the proportion of the parts replaced last time; returning the replaced parts in the pending combination to the pending production database; then jumping to step S5;
if the loop is not continued, the pending combination is set to the preferred combination U ═ DiPjHk… …, and performing scheduling in a preferred combination, the parts in the database to be scheduled are set as non-scheduled parts.
To implement the method described in this embodiment, this embodiment provides an efficient and intelligent customized furniture order scheduling apparatus, which includes:
the order acquisition module is used for acquiring a newly added order to obtain a furniture design drawing contained in the newly added order;
the order decomposition module is used for splitting the newly added order into minimum parts according to the furniture design drawing and marking part information; the part information comprises part names, part categories, color categories, sizes, outer contour types, hole and groove types and order characteristic information of corresponding orders; the order characteristic information comprises an order number and a delivery date;
the to-be-scheduled production database processing module is used for storing newly-added order parts, non-scheduled production parts and reworked parts in the to-be-scheduled production database and removing order-returned order parts from the to-be-scheduled production database;
the test combination initialization module is used for extracting a plurality of parts from the database to be scheduled to be produced to be combined into an initial test combination, and setting the initial test combination as an initialized undetermined combination;
the test combination updating module is used for extracting part of parts in the database to be scheduled and replacing part of parts which are not replaced in the database to be scheduled to combine into a new test combination; returning the replaced parts in the pending combination to the pending production database;
the combination scoring module is used for analyzing the current test combination to obtain an evaluation score;
the score comparison module is used for comparing the evaluation score of the current test combination with the evaluation score of the undetermined combination: if the evaluation score of the current test combination is higher than that of the undetermined combination, updating the undetermined combination into the current test combination; if the evaluation score of the current test combination is lower than or equal to the evaluation score of the undetermined combination, the original undetermined combination is reserved;
and the output module is used for setting the combination to be determined as the preferred combination when the cycle is finished, performing production scheduling according to the preferred combination, and setting the parts in the database to be scheduled as the parts not scheduled.
Example two
The difference between the efficient and intelligent customized furniture order scheduling method of the embodiment one is as follows: in the embodiment, an expert system knowledge base comprising a plurality of rule units is set; in step S4, selecting more than one rule unit in the expert system knowledge base, and extracting a plurality of parts from the database to be scheduled to combine into an initial test combination according to the selected rule units;
after the preferred combination is obtained in step S7, the rule units of the expert system knowledge base are updated according to the preferred combination, or new rule units are generated and added to the expert system knowledge base.
The expert system knowledge base may include: a completion deadline rule unit, a process selection rule unit, a resource selection rule unit, a maximum equipment utilization rate rule unit, a minimum task waiting time rule unit, a minimum processing interval rule unit, and the like.
The expert system knowledge base can set a large number of production scheduling rules, including production scheduling knowledge and experience and features extracted by obtaining the optimal combination each time, so that the initial test combination is combined by combining the expert system knowledge base, a scheme close to the optimal combination can be obtained, and the time for solving the optimal combination is greatly shortened. After the optimal combination is solved, the rules are induced and adjusted, and the expert system knowledge base is continuously optimized and perfected in an iterative mode.
The rest of the embodiment is the same as the first embodiment.
EXAMPLE III
The present embodiment is a storage medium, wherein the storage medium stores a computer program, and the computer program, when executed by a processor, causes the processor to execute the method for arranging an order for an intelligent customized furniture according to the first embodiment or the second embodiment.
Example four
The embodiment is a computing device, which includes a processor and a memory for storing a program executable by the processor, and when the processor executes the program stored in the memory, the efficient intelligent customized furniture order scheduling method described in the first embodiment or the second embodiment is implemented.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (10)
1. An efficient intelligent customized furniture order scheduling method is characterized by comprising the following steps: the method comprises the following steps:
s1, acquiring a newly added order to obtain a furniture design drawing included in the newly added order;
s2, splitting the newly added order into minimum parts according to furniture design drawings, and marking part information; the part information comprises part names, part categories, color categories, sizes, outer contour types, hole and groove types and order characteristic information of corresponding orders; the order characteristic information comprises an order number and a delivery date;
s3, storing newly added order parts, unmanaged parts and reworked parts in a to-be-scheduled production database, and removing order returned order parts from the to-be-scheduled production database;
s4, extracting a plurality of parts from the database to be scheduled to combine into an initial test combination, and setting the initial test combination as an initialized undetermined combination;
s5, analyzing the current test combination to obtain an evaluation score;
and step S6, judging whether the current test combination is the initial test combination:
if yes, directly jumping to the step S7;
otherwise, the evaluation score of the current trial combination is compared with the evaluation score of the pending combination: if the evaluation score of the current test combination is higher than that of the undetermined combination, updating the undetermined combination into the current test combination; if the evaluation score of the current test combination is lower than or equal to the evaluation score of the undetermined combination, the original undetermined combination is reserved;
and step S7, judging whether to continue circulation:
if yes, extracting part of parts in the database to be scheduled to produce, and replacing part of parts which are not replaced in the to-be-scheduled combination to form a new test combination; returning the replaced parts in the pending combination to the pending production database; then jumping to step S5;
otherwise, the combination to be determined is set as the preferred combination, the production is performed according to the preferred combination, and the parts in the database to be produced are set as the parts which are not produced.
2. The efficient intelligent customized furniture order scheduling method according to claim 1, wherein: in the step S2, splitting the newly added order into minimum parts according to the furniture design drawing, which means: splitting the newly added order into various furniture, splitting the furniture into minimum parts according to a furniture design drawing, wherein a part set of the newly added order is represented by I:
I＝{DiPjHk}(i＝1,2,3,…n，j＝1,2,3,…n，k＝1,2,3,…n)
wherein DiIndicates an order number, PjDenotes the name of furniture HkRepresenting the smallest part.
3. The efficient intelligent customized furniture order scheduling method according to claim 1, wherein: in the step S5, analyzing the current test combination to obtain an evaluation score, which means:
firstly, analyzing the reasonable degree of combination of the current test combination to obtain a score A:
A＝A1+A2+A3+A4+A5+A6+A7+A8
wherein A is1Representing a part color category score; a. the2Representing the same category score of the parts; a. the3A score representing the delivery date tension level; a. the4Representing a part quantity score; a. the5The score of the similarity degree of the sizes of the parts is expressed; a. the6Representing a part type facies proximity score; a. the7The score of the similarity degree of the outer contour types of the parts is represented; a. the8The score of the similarity degree of the types of the hole grooves of the parts is represented;
and analyzing the production capacity of the test combination to obtain a score B:
B＝B1+B2+B3+B4+B5
wherein, B1Representing the score of the sufficiency of the materials corresponding to the parts; b is2Representing the reasonable degree score of the arrangement of the parts corresponding to the processing equipment; b is3Indicating that the parts correspond to the production workersRanking the reasonable degree score; b is4Representing the productivity efficiency score of the processing equipment corresponding to the part; b is5A score representing the degree of man-hour engagement;
and then adding the score A and the score B according to a set weight to obtain an evaluation score:
Score＝α·A+(1-α)·B
wherein α is a reduction factor.
4. The efficient intelligent customized furniture order scheduling method according to claim 3, wherein: in the score B, B1The acquisition method comprises the following steps: calculating the materials and the quantity of the materials required by production according to the part types, the color types and the sizes of all parts in the test combination; comparing the calculated materials and the quantity of each material with the stock of the materials in the material database to obtain a component corresponding material sufficiency degree score B1；
B2The acquisition method comprises the following steps: obtaining processing equipment required by production through part types, color types, sizes, outer contour types and hole and groove types of all parts in the test combination; obtaining the scheduling condition of the processing equipment required by production so as to obtain the reasonable degree score B of the arrangement of the processing equipment corresponding to the part2；
B3The acquisition method comprises the following steps: obtaining a corresponding production processing station through the part category, the color category, the size, the outer contour type and the hole and groove type of each part in the test combination; obtaining the scheduling condition of workers producing corresponding processing stations, thereby obtaining the reasonable degree score B of arrangement of the workers producing corresponding parts3；
B4The acquisition method comprises the following steps: obtaining processing equipment required by production through part types, color types, sizes, outer contour types and hole and groove types of all parts in the test combination; obtaining the production condition of the processing equipment required by production, comparing the actual yield of the processing equipment required by production with the predicted yield of the experimental combination with the design yield of the processing equipment to obtain a capacity efficiency score B of the processing equipment corresponding to the part4；
B5Acquisition methodComprises the following steps: calculating the expected production time of all parts in the test combination on the processing equipment required by production or the processing station corresponding to the production so as to obtain a working hour matching degree score B5。
5. The efficient intelligent customized furniture order scheduling method according to claim 1, wherein: in the step S7, the step of determining whether to continue the loop includes: judging the evaluation score of the undetermined combination: if the evaluation score of the undetermined combination is higher than the set optimal evaluation score, or the variance between the mean value of the evaluation scores of the continuous N-generation test combinations and the evaluation score of the current test combination is smaller than the set threshold, ending the circulation; otherwise, the loop continues.
6. The efficient intelligent customized furniture order scheduling method according to claim 1, wherein: in the step S7, extracting some parts in the database to be scheduled means: respectively judging the priority of each part in the to-be-scheduled production database; extracting part of parts with the highest priority in a database to be scheduled;
in step S7, the replaced parts ratio is less than or equal to the parts ratio replaced last time.
7. The efficient intelligent customized furniture order scheduling method of claim 6, wherein: establishing an expert system knowledge base comprising a plurality of rule units; in the step S4, more than one rule unit in the expert system knowledge base is selected, and a plurality of parts are extracted from the database to be scheduled according to the selected rule units to be combined into an initial test combination;
after the preferred combination is obtained in step S7, the rule units of the expert system knowledge base are updated according to the preferred combination, or new rule units are generated and added to the expert system knowledge base.
8. The utility model provides a high-efficient intelligence customization furniture order scheduling device which characterized in that includes:
the order acquisition module is used for acquiring a newly added order to obtain a furniture design drawing contained in the newly added order;
the order decomposition module is used for splitting the newly added order into minimum parts according to the furniture design drawing and marking part information; the part information comprises part names, part categories, color categories, sizes, outer contour types, hole and groove types and order characteristic information of corresponding orders; the order characteristic information comprises an order number and a delivery date;
the to-be-scheduled production database processing module is used for storing newly-added order parts, non-scheduled production parts and reworked parts in the to-be-scheduled production database and removing order-returned order parts from the to-be-scheduled production database;
the test combination initialization module is used for extracting a plurality of parts from the database to be scheduled to be produced to be combined into an initial test combination, and setting the initial test combination as an initialized undetermined combination;
the test combination updating module is used for extracting part of parts in the database to be scheduled and replacing part of parts which are not replaced in the database to be scheduled to combine into a new test combination; returning the replaced parts in the pending combination to the pending production database;
the combination scoring module is used for analyzing the current test combination to obtain an evaluation score;
the score comparison module is used for comparing the evaluation score of the current test combination with the evaluation score of the undetermined combination: if the evaluation score of the current test combination is higher than that of the undetermined combination, updating the undetermined combination into the current test combination; if the evaluation score of the current test combination is lower than or equal to the evaluation score of the undetermined combination, the original undetermined combination is reserved;
and the output module is used for setting the combination to be determined as the preferred combination when the cycle is finished, performing production scheduling according to the preferred combination, and setting the parts in the database to be scheduled as the parts not scheduled.
9. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, causes the processor to perform the method of efficient intelligent custom furniture order scheduling of any of claims 1-7.
10. A computing device comprising a processor and a memory for storing processor-executable programs, wherein the processor, when executing the programs stored in the memory, implements the method for efficient intelligent custom furniture order scheduling of any of claims 1-7.
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